A GPU accelerated RNA-RNA interaction program
Date
2021
Authors
Gildemaster, Brandon, author
Rajopadhye, Sanjay, advisor
Chitsaz, Hamidreza, committee member
Abdo, Zaid, committee member
Journal Title
Journal ISSN
Volume Title
Abstract
RNA-RNA interaction (RRI) is important in processes like gene regulation, and is known to play roles in diseases including cancer and Alzheimer's. Large RRI computations run for days, weeks or even months, because the algorithms have time and space complexity of, respectively, O(N3M3) and O(N2M2), for sequences length N and M, and there is a need for high-throughput RRI tools. GPU parallelization of such algorithms is a challenge. We first show that the most computationally expensive part of base pair maximization (BPM) algorithms comprises O(N3) instances of upper banded tropical matrix products. We develop the first GPU library for this attaining close to theoretical machine peak (TMP). We next optimize other (fifth degree polynomial) terms in the computation and develop the first GPU implementation of the complete BPMax algorithm. We attain 12% of GPU TMP, a significant speedup over the original parallel CPU implementation, which attains less than 1% of CPU TMP. We also perform a large scale study of three small viral RNAs, hypothesized to be relevant to COVID-19.